Spectral imaging sensors capture and process multiple wavelength bands across the electromagnetic spectrum, as compared to an ordinary camera or imaging sensor that captures light across the visible spectrum formed of red, green and blue (RGB) wavelengths. Spectral imaging may incorporate the infrared, the visible spectrum, ultraviolet, x-rays and a combination of image data in the visible and non-visible bands simultaneously. Hyperspectral imaging is an extension of normal spectral imaging and considered by those skilled in the art to combine spectroscopy and digital photography, allowing data collection for the complete spectrum and possibly additional information about the subject material properties. In hyperspectral imaging, the complete spectrum over hundreds of narrow wavelength bands is collected at every pixel in an image plane. Special hyperspectral imaging sensors or cameras include spectrometers that capture hundreds of wavelength bands for each pixel, which are interpreted as the complete spectrum. The spectral image data from a hyperspectral imaging sensor has a fine wavelength resolution (typically 1, 5 or 20 nm spectral resolution), covers a wide range of wavelengths, and may measure continuous spectral bands. Because certain objects leave unique spectral “fingerprints” in the electromagnetic spectrum, also called “spectral signatures,” these spectral fingerprints enable identification and analysis of materials that make up a scanned object. For example, a spectral fingerprint or signature for oil may help geologists find new oil fields. Likewise, the spectral signature for a certain type of metal or alloy may help engineers identify structural and material characteristics in a bridge and the structural and material differences among various sections in the bridge.
Temporal imaging or temporal characterization, as it is sometimes called, occurs when a series of images are taken at different times. The correlation between those images is often used to monitor the dynamic changes of the object. The term hypertemporal imaging usually refers to very high temporal resolution images that can detect high frequency intensity time varying changes. For example, a hypertemporal imaging system may detect minute structural changes, such as vibration signatures in a bridge. By processing these vibrations over time, it may be possible to determine if there is some material instability or weakness, depending on the material characteristics of the bridge construction in that area of the bridge where the vibrational changes are being analyzed on a pixel by pixel basis. It may also be possible to detect vibration signatures of vehicles and machinery to monitor their health and status. Other possibilities include characterizing surface and subsurface defects in the earth or in large objects.